Assessing uncertainty propagation through physically based models of soil water flow and solute transport

By James D. Brown, Gerard B. M. Heuvelink. 2006

94 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/3f693a129e6812b80c313a8c03589a040bd16bc7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. B. Ataie‐Ashtiani
2. Craig T. Simmons
3. M. Rajabi

In Environmental Engineering

1. Dominique Arrouays
2. B. Ataie‐Ashtiani
3. Manuel P. Martin
4. Craig T. Simmons
5. M. Rajabi
6. Jean-Pierre Renaud
7. Sabine Grunwald

Citations in the corpus

• Estimating forest soil bulk density using boosted regression modelling (2010, background): “Calhoun et al. (2001) show that the combination of continuous variables (laboratory data) and nominal ones (site factor and morphological descriptors) improve the prediction of soil bulk density. Model G10 through incorporating both kinds of inputs (continuous and discrete variables) gave the best r”
• Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations (2015, background): “Quantifying this uncertainty is known as uncertainty propagation (UP) analysis (Brown and Heuvelink, 2006).”